Cytomining Ecosystem Software Landscape Analysis: Data Profile

Dataset statistics

Number of variables	32
Number of observations	1123
Missing cells	3026
Missing cells (%)	8.4%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	273.2 KiB
Average record size in memory	249.1 B

Variable types

Text	5
Numeric	14
Unsupported	7
Categorical	3
DateTime	2
Boolean	1

Alerts

`GitHub Repository ID` is highly overall correlated with `Duration Created to Now in Years`	High correlation
`GitHub Stars` is highly overall correlated with `GitHub Forks` and 7 other fields	High correlation
`GitHub Forks` is highly overall correlated with `GitHub Stars` and 7 other fields	High correlation
`GitHub Subscribers` is highly overall correlated with `GitHub Stars` and 7 other fields	High correlation
`GitHub Open Issues` is highly overall correlated with `GitHub Stars` and 7 other fields	High correlation
`GitHub Contributors` is highly overall correlated with `GitHub Stars` and 7 other fields	High correlation
`GitHub Network Count` is highly overall correlated with `GitHub Stars` and 7 other fields	High correlation
`Repository Size (KB)` is highly overall correlated with `total lines of GitHub detected code` and 1 other fields	High correlation
`Duration Created to Now in Years` is highly overall correlated with `GitHub Repository ID`	High correlation
`GitHub Stars (Log Scale)` is highly overall correlated with `GitHub Stars` and 8 other fields	High correlation
`total lines of GitHub detected code` is highly overall correlated with `Repository Size (KB)` and 2 other fields	High correlation
`total lines of GitHub detected code (Log Scale)` is highly overall correlated with `Repository Size (KB)` and 1 other fields	High correlation
`GitHub Forks (Log Scale)` is highly overall correlated with `GitHub Stars` and 8 other fields	High correlation
`GitHub Open Issues (Log Scale)` is highly overall correlated with `GitHub Stars` and 7 other fields	High correlation
`category` is highly overall correlated with `GitHub Stars (Log Scale)` and 1 other fields	High correlation
`Primary language` is highly overall correlated with `total lines of GitHub detected code`	High correlation
`GitHub Repo Archived` is highly imbalanced (90.9%)	Imbalance
`category` is highly imbalanced (75.0%)	Imbalance
`Project Homepage` has 539 (48.0%) missing values	Missing
`GitHub License Type` has 551 (49.1%) missing values	Missing
`GitHub Description` has 54 (4.8%) missing values	Missing
`GitHub Organization` has 729 (64.9%) missing values	Missing
`GitHub Stars (Log Scale)` has 44 (3.9%) missing values	Missing
`GitHub Forks (Log Scale)` has 435 (38.7%) missing values	Missing
`GitHub Open Issues (Log Scale)` has 674 (60.0%) missing values	Missing
`GitHub Stars` is highly skewed (γ1 = 21.55540447)	Skewed
`GitHub Forks` is highly skewed (γ1 = 25.30444087)	Skewed
`GitHub Subscribers` is highly skewed (γ1 = 22.78021783)	Skewed
`GitHub Network Count` is highly skewed (γ1 = 25.30419643)	Skewed
`total lines of GitHub detected code` is highly skewed (γ1 = 24.44181837)	Skewed
`GitHub Repository ID` has unique values	Unique
`Project Repo URL` has unique values	Unique
`Date Created` has unique values	Unique
`Date Most Recent Commit` has unique values	Unique
`Project Landscape Category` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`GitHub Topics` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`GitHub Detected Languages` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Duration Created to Most Recent Commit` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Duration Created to Now` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Duration Most Recent Commit to Now` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`Negative Duration Most Recent Commit to Now` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`GitHub Stars` has 44 (3.9%) zeros	Zeros
`GitHub Forks` has 435 (38.7%) zeros	Zeros
`GitHub Subscribers` has 52 (4.6%) zeros	Zeros
`GitHub Open Issues` has 674 (60.0%) zeros	Zeros
`GitHub Contributors` has 27 (2.4%) zeros	Zeros
`GitHub Network Count` has 435 (38.7%) zeros	Zeros
`GitHub Stars (Log Scale)` has 316 (28.1%) zeros	Zeros
`GitHub Forks (Log Scale)` has 167 (14.9%) zeros	Zeros
`GitHub Open Issues (Log Scale)` has 125 (11.1%) zeros	Zeros

Reproduction

Analysis started	2023-10-19 21:29:54.076023
Analysis finished	2023-10-19 21:30:09.107936
Duration	15.03 seconds
Software version	ydata-profiling vv4.6.0
Download configuration	config.json

Project Name
Text

Distinct	1090
Distinct (%)	97.1%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Length

Max length	100
Median length	65
Mean length	15.050757
Min length	3

Characters and Unicode

Total characters	16902
Distinct characters	65
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1065 ?
Unique (%)	94.8%

Sample

1st row	pandas
2nd row	numpy
3rd row	arrow
4th row	duckdb
5th row	parquet-mr

Value	Count	Frequency (%)
single-cell-analysis	8	0.7%
single-cell-rna-seq-analysis	7	0.6%
single_cell_analysis	7	0.6%
singlecellanalysis	4	0.4%
single-cell-rna-seq	4	0.4%
singlecell	3	0.3%
orchestratingsinglecellanalysis	3	0.3%
single-cell-rna-sequencing-analysis	2	0.2%
cytominer	2	0.2%
spectre	2	0.2%
Other values (1060)	1081	96.3%

Most occurring characters

Value	Count	Frequency (%)
e	1443	8.5%
l	1339	7.9%
s	1259	7.4%
i	1025	6.1%
a	1012	6.0%
n	949	5.6%
-	847	5.0%
c	778	4.6%
o	695	4.1%
t	617	3.7%
Other values (55)	6938	41.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	12372	73.2%
Uppercase Letter	2819	16.7%
Dash Punctuation	847	5.0%
Connector Punctuation	431	2.5%
Decimal Number	413	2.4%
Other Punctuation	20	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1443	11.7%
l	1339	10.8%
s	1259	10.2%
i	1025	8.3%
a	1012	8.2%
n	949	7.7%
c	778	6.3%
o	695	5.6%
t	617	5.0%
r	573	4.6%
Other values (16)	2682	21.7%

Uppercase Letter

Value	Count	Frequency (%)
A	427	15.1%
C	394	14.0%
S	374	13.3%
R	231	8.2%
N	205	7.3%
M	132	4.7%
T	129	4.6%
P	128	4.5%
I	113	4.0%
D	105	3.7%
Other values (16)	581	20.6%

Decimal Number

Value	Count	Frequency (%)
2	156	37.8%
0	100	24.2%
1	72	17.4%
3	22	5.3%
9	21	5.1%
8	14	3.4%
4	11	2.7%
7	8	1.9%
6	5	1.2%
5	4	1.0%

Dash Punctuation

Value	Count	Frequency (%)
-	847	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	431	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	20	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	15191	89.9%
Common	1711	10.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1443	9.5%
l	1339	8.8%
s	1259	8.3%
i	1025	6.7%
a	1012	6.7%
n	949	6.2%
c	778	5.1%
o	695	4.6%
t	617	4.1%
r	573	3.8%
Other values (42)	5501	36.2%

Common

Value	Count	Frequency (%)
-	847	49.5%
_	431	25.2%
2	156	9.1%
0	100	5.8%
1	72	4.2%
3	22	1.3%
9	21	1.2%
.	20	1.2%
8	14	0.8%
4	11	0.6%
Other values (3)	17	1.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	16902	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1443	8.5%
l	1339	7.9%
s	1259	7.4%
i	1025	6.1%
a	1012	6.0%
n	949	5.6%
-	847	5.0%
c	778	4.6%
o	695	4.1%
t	617	3.7%
Other values (55)	6938	41.0%

GitHub Repository ID
Real number (ℝ)

HIGH CORRELATION UNIQUE

Distinct	1123
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.7923865 × 10⁸

Minimum	858127
Maximum	7.0306429 × 10⁸
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	858127
5-th percentile	48407428
Q1	1.4014133 × 10⁸
median	2.5217638 × 10⁸
Q3	3.8810811 × 10⁸
95-th percentile	6.0591363 × 10⁸
Maximum	7.0306429 × 10⁸
Range	7.0220617 × 10⁸
Interquartile range (IQR)	2.4796679 × 10⁸

Descriptive statistics

Standard deviation	1.7117573 × 10⁸
Coefficient of variation (CV)	0.61300875
Kurtosis	-0.58841698
Mean	2.7923865 × 10⁸
Median Absolute Deviation (MAD)	1.2213142 × 10⁸
Skewness	0.54510555
Sum	3.13585 × 10¹¹
Variance	2.9301131 × 10¹⁶
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
858127	1	0.1%
292773252	1	0.1%
255056675	1	0.1%
146028869	1	0.1%
232201771	1	0.1%
167464808	1	0.1%
156759735	1	0.1%
255893503	1	0.1%
339741407	1	0.1%
188461334	1	0.1%
Other values (1113)	1113	99.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
858127	1	0.1%
908607	1	0.1%
925122	1	0.1%
1571820	1	0.1%
2136580	1	0.1%
2290781	1	0.1%
2425273	1	0.1%
4890816	1	0.1%
5771522	1	0.1%
8678018	1	0.1%

Value	Count	Frequency (%)
703064293	1	0.1%
690579583	1	0.1%
689948460	1	0.1%
682462552	1	0.1%
681597755	1	0.1%
679608830	1	0.1%
678475435	1	0.1%
678200716	1	0.1%
677900044	1	0.1%
677883930	1	0.1%

Project Homepage
Text

MISSING

Distinct	206
Distinct (%)	35.3%
Missing	539
Missing (%)	48.0%
Memory size	8.9 KiB

Length

Max length	116
Median length	0
Mean length	13.777397
Min length	0

Characters and Unicode

Total characters	8046
Distinct characters	65
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	204 ?
Unique (%)	34.9%

Sample

1st row	https://pandas.pydata.org
2nd row	https://numpy.org
3rd row	https://arrow.apache.org/
4th row	http://www.duckdb.org
5th row

Value	Count	Frequency (%)
http://nasqar.abudhabi.nyu.edu	2	1.0%
https://combine-lab.github.io/salmon	1	0.5%
https://www.scrna-tools.org	1	0.5%
https://arrow.apache.org	1	0.5%
http://www.duckdb.org	1	0.5%
https://snakemake.readthedocs.io	1	0.5%
http://www.satijalab.org/seurat	1	0.5%
https://napari.org	1	0.5%
https://scanpy.readthedocs.io	1	0.5%
http://scvi-tools.org	1	0.5%
Other values (195)	195	94.7%

Most occurring characters

Value	Count	Frequency (%)
t	757	9.4%
/	727	9.0%
s	489	6.1%
i	475	5.9%
o	461	5.7%
e	413	5.1%
.	408	5.1%
h	406	5.0%
a	366	4.5%
p	308	3.8%
Other values (55)	3236	40.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6072	75.5%
Other Punctuation	1339	16.6%
Decimal Number	291	3.6%
Uppercase Letter	201	2.5%
Dash Punctuation	124	1.5%
Connector Punctuation	17	0.2%
Open Punctuation	1	< 0.1%
Close Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	757	12.5%
s	489	8.1%
i	475	7.8%
o	461	7.6%
e	413	6.8%
h	406	6.7%
a	366	6.0%
p	308	5.1%
c	293	4.8%
r	283	4.7%
Other values (16)	1821	30.0%

Uppercase Letter

Value	Count	Frequency (%)
C	29	14.4%
S	27	13.4%
A	23	11.4%
R	16	8.0%
M	11	5.5%
T	10	5.0%
I	9	4.5%
N	9	4.5%
D	9	4.5%
O	9	4.5%
Other values (12)	49	24.4%

Decimal Number

Value	Count	Frequency (%)
1	63	21.6%
0	58	19.9%
2	42	14.4%
3	23	7.9%
4	22	7.6%
6	19	6.5%
8	17	5.8%
7	16	5.5%
9	16	5.5%
5	15	5.2%

Other Punctuation

Value	Count	Frequency (%)
/	727	54.3%
.	408	30.5%
:	204	15.2%

Dash Punctuation

Value	Count	Frequency (%)
-	124	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	17	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	1	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6273	78.0%
Common	1773	22.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	757	12.1%
s	489	7.8%
i	475	7.6%
o	461	7.3%
e	413	6.6%
h	406	6.5%
a	366	5.8%
p	308	4.9%
c	293	4.7%
r	283	4.5%
Other values (38)	2022	32.2%

Common

Value	Count	Frequency (%)
/	727	41.0%
.	408	23.0%
:	204	11.5%
-	124	7.0%
1	63	3.6%
0	58	3.3%
2	42	2.4%
3	23	1.3%
4	22	1.2%
6	19	1.1%
Other values (7)	83	4.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8046	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	757	9.4%
/	727	9.0%
s	489	6.1%
i	475	5.9%
o	461	5.7%
e	413	5.1%
.	408	5.1%
h	406	5.0%
a	366	4.5%
p	308	3.8%
Other values (55)	3236	40.2%

Project Repo URL
Text

UNIQUE

Distinct	1123
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Length

Max length	157
Median length	91
Mean length	45.211932
Min length	28

Characters and Unicode

Total characters	50773
Distinct characters	67
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1123 ?
Unique (%)	100.0%

Sample

1st row	https://github.com/pandas-dev/pandas
2nd row	https://github.com/numpy/numpy
3rd row	https://github.com/apache/arrow
4th row	https://github.com/duckdb/duckdb
5th row	https://github.com/apache/parquet-mr

Value	Count	Frequency (%)
https://github.com/pandas-dev/pandas	1	0.1%
https://github.com/scverse/scanpy	1	0.1%
https://github.com/duckdb/duckdb	1	0.1%
https://github.com/apache/parquet-mr	1	0.1%
https://github.com/snakemake/snakemake	1	0.1%
https://github.com/satijalab/seurat	1	0.1%
https://github.com/napari/napari	1	0.1%
https://github.com/chris-mcginnis-ucsf/doubletfinder	1	0.1%
https://github.com/theislab/single-cell-tutorial	1	0.1%
https://github.com/sqjin/cellchat	1	0.1%
Other values (1113)	1113	99.1%

Most occurring characters

Value	Count	Frequency (%)
/	4492	8.8%
t	4402	8.7%
i	3032	6.0%
s	2940	5.8%
h	2809	5.5%
o	2442	4.8%
c	2302	4.5%
e	2218	4.4%
a	2211	4.4%
l	1917	3.8%
Other values (57)	22008	43.3%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	37999	74.8%
Other Punctuation	6758	13.3%
Uppercase Letter	3741	7.4%
Dash Punctuation	1105	2.2%
Decimal Number	739	1.5%
Connector Punctuation	431	0.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	4402	11.6%
i	3032	8.0%
s	2940	7.7%
h	2809	7.4%
o	2442	6.4%
c	2302	6.1%
e	2218	5.8%
a	2211	5.8%
l	1917	5.0%
g	1817	4.8%
Other values (16)	11909	31.3%

Uppercase Letter

Value	Count	Frequency (%)
A	476	12.7%
C	466	12.5%
S	451	12.1%
R	255	6.8%
N	238	6.4%
M	193	5.2%
L	173	4.6%
T	173	4.6%
P	157	4.2%
I	157	4.2%
Other values (16)	1002	26.8%

Decimal Number

Value	Count	Frequency (%)
2	196	26.5%
0	153	20.7%
1	127	17.2%
9	54	7.3%
3	47	6.4%
8	43	5.8%
4	39	5.3%
7	31	4.2%
5	27	3.7%
6	22	3.0%

Other Punctuation

Value	Count	Frequency (%)
/	4492	66.5%
.	1143	16.9%
:	1123	16.6%

Dash Punctuation

Value	Count	Frequency (%)
-	1105	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	431	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	41740	82.2%
Common	9033	17.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	4402	10.5%
i	3032	7.3%
s	2940	7.0%
h	2809	6.7%
o	2442	5.9%
c	2302	5.5%
e	2218	5.3%
a	2211	5.3%
l	1917	4.6%
g	1817	4.4%
Other values (42)	15650	37.5%

Common

Value	Count	Frequency (%)
/	4492	49.7%
.	1143	12.7%
:	1123	12.4%
-	1105	12.2%
_	431	4.8%
2	196	2.2%
0	153	1.7%
1	127	1.4%
9	54	0.6%
3	47	0.5%
Other values (5)	162	1.8%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	50773	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
/	4492	8.8%
t	4402	8.7%
i	3032	6.0%
s	2940	5.8%
h	2809	5.5%
o	2442	4.8%
c	2302	4.5%
e	2218	4.4%
a	2211	4.4%
l	1917	3.8%
Other values (57)	22008	43.3%

Project Landscape Category
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

GitHub Stars
Real number (ℝ)

HIGH CORRELATION SKEWED ZEROS

Distinct	160
Distinct (%)	14.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	118.76313

Minimum	0
Maximum	40031
Zeros	44
Zeros (%)	3.9%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	3
Q3	16
95-th percentile	193.7
Maximum	40031
Range	40031
Interquartile range (IQR)	15

Descriptive statistics

Standard deviation	1505.2762
Coefficient of variation (CV)	12.674608
Kurtosis	512.24869
Mean	118.76313
Median Absolute Deviation (MAD)	2
Skewness	21.555404
Sum	133371
Variance	2265856.4
Monotonicity	Decreasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	316	28.1%
2	130	11.6%
3	88	7.8%
4	66	5.9%
0	44	3.9%
5	39	3.5%
6	28	2.5%
8	24	2.1%
7	20	1.8%
9	18	1.6%
Other values (150)	350	31.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	44	3.9%
1	316	28.1%
2	130	11.6%
3	88	7.8%
4	66	5.9%
5	39	3.5%
6	28	2.5%
7	20	1.8%
8	24	2.1%
9	18	1.6%

Value	Count	Frequency (%)
40031	1	0.1%
24741	1	0.1%
12614	1	0.1%
12393	1	0.1%
2179	1	0.1%
1955	1	0.1%
1947	1	0.1%
1912	1	0.1%
1612	1	0.1%
1592	1	0.1%

GitHub Forks
Real number (ℝ)

HIGH CORRELATION SKEWED ZEROS

Distinct	96
Distinct (%)	8.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	38.96171

Minimum	0
Maximum	16810
Zeros	435
Zeros (%)	38.7%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	6
95-th percentile	52.9
Maximum	16810
Range	16810
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	575.00662
Coefficient of variation (CV)	14.758249
Kurtosis	691.20536
Mean	38.96171
Median Absolute Deviation (MAD)	1
Skewness	25.304441
Sum	43754
Variance	330632.61
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	435	38.7%
1	167	14.9%
2	103	9.2%
3	64	5.7%
4	45	4.0%
6	30	2.7%
5	25	2.2%
8	23	2.0%
9	19	1.7%
7	18	1.6%
Other values (86)	194	17.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	435	38.7%
1	167	14.9%
2	103	9.2%
3	64	5.7%
4	45	4.0%
5	25	2.2%
6	30	2.7%
7	18	1.6%
8	23	2.0%
9	19	1.7%

Value	Count	Frequency (%)
16810	1	0.1%
8647	1	0.1%
3096	1	0.1%
1332	1	0.1%
1157	1	0.1%
851	1	0.1%
536	1	0.1%
474	1	0.1%
473	1	0.1%
422	1	0.1%

GitHub Subscribers
Real number (ℝ)

HIGH CORRELATION SKEWED ZEROS

Distinct	45
Distinct (%)	4.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	6.2288513

Minimum	0
Maximum	1121
Zeros	52
Zeros (%)	4.6%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	2
Q3	4
95-th percentile	15
Maximum	1121
Range	1121
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	40.027421
Coefficient of variation (CV)	6.4261321
Kurtosis	583.17272
Mean	6.2288513
Median Absolute Deviation (MAD)	1
Skewness	22.780218
Sum	6995
Variance	1602.1945
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=45)

Value	Count	Frequency (%)
1	363	32.3%
2	247	22.0%
3	116	10.3%
4	74	6.6%
0	52	4.6%
5	47	4.2%
6	37	3.3%
7	34	3.0%
8	24	2.1%
9	19	1.7%
Other values (35)	110	9.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	52	4.6%
1	363	32.3%
2	247	22.0%
3	116	10.3%
4	74	6.6%
5	47	4.2%
6	37	3.3%
7	34	3.0%
8	24	2.1%
9	19	1.7%

Value	Count	Frequency (%)
1121	1	0.1%
595	1	0.1%
351	1	0.1%
157	1	0.1%
95	1	0.1%
86	1	0.1%
78	1	0.1%
54	1	0.1%
51	1	0.1%
49	1	0.1%

GitHub Open Issues
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	80
Distinct (%)	7.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	18.506679

Minimum	0
Maximum	3908
Zeros	674
Zeros (%)	60.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	2
95-th percentile	31.9
Maximum	3908
Range	3908
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	181.0509
Coefficient of variation (CV)	9.7830035
Kurtosis	354.14214
Mean	18.506679
Median Absolute Deviation (MAD)	0
Skewness	17.999386
Sum	20783
Variance	32779.428
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	674	60.0%
1	125	11.1%
2	53	4.7%
3	33	2.9%
6	26	2.3%
4	26	2.3%
5	14	1.2%
8	14	1.2%
7	13	1.2%
11	8	0.7%
Other values (70)	137	12.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	674	60.0%
1	125	11.1%
2	53	4.7%
3	33	2.9%
4	26	2.3%
5	14	1.2%
6	26	2.3%
7	13	1.2%
8	14	1.2%
9	7	0.6%

Value	Count	Frequency (%)
3908	1	0.1%
3656	1	0.1%
2193	1	0.1%
1019	1	0.1%
906	1	0.1%
701	1	0.1%
547	1	0.1%
424	1	0.1%
363	1	0.1%
309	1	0.1%

GitHub Contributors
Real number (ℝ)

HIGH CORRELATION ZEROS

Distinct	38
Distinct (%)	3.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	4.6073019

Minimum	0
Maximum	435
Zeros	27
Zeros (%)	2.4%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	1
median	1
Q3	3
95-th percentile	10
Maximum	435
Range	435
Interquartile range (IQR)	2

Descriptive statistics

Standard deviation	25.443233
Coefficient of variation (CV)	5.5223717
Kurtosis	190.13087
Mean	4.6073019
Median Absolute Deviation (MAD)	0
Skewness	13.186791
Sum	5174
Variance	647.35813
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=38)

Value	Count	Frequency (%)
1	659	58.7%
2	143	12.7%
3	102	9.1%
4	60	5.3%
5	29	2.6%
0	27	2.4%
6	15	1.3%
7	11	1.0%
11	10	0.9%
10	10	0.9%
Other values (28)	57	5.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	27	2.4%
1	659	58.7%
2	143	12.7%
3	102	9.1%
4	60	5.3%
5	29	2.6%
6	15	1.3%
7	11	1.0%
8	9	0.8%
9	8	0.7%

Value	Count	Frequency (%)
435	1	0.1%
411	1	0.1%
367	1	0.1%
280	1	0.1%
253	1	0.1%
190	1	0.1%
150	1	0.1%
125	1	0.1%
83	1	0.1%
79	1	0.1%

GitHub License Type
Categorical

MISSING

Distinct	15
Distinct (%)	2.6%
Missing	551
Missing (%)	49.1%
Memory size	8.9 KiB

MIT	211
GPL-3.0	163
NOASSERTION	73
BSD-3-Clause	49
Apache-2.0	29
Other values (10)	47

Length

Max length	18
Median length	12
Mean length	6.7412587
Min length	3

Characters and Unicode

Total characters	3856
Distinct characters	36
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	4 ?
Unique (%)	0.7%

Sample

1st row	BSD-3-Clause
2nd row	BSD-3-Clause
3rd row	Apache-2.0
4th row	MIT
5th row	Apache-2.0

Common Values

Value	Count	Frequency (%)
MIT	211	18.8%
GPL-3.0	163	14.5%
NOASSERTION	73	6.5%
BSD-3-Clause	49	4.4%
Apache-2.0	29	2.6%
CC0-1.0	13	1.2%
AGPL-3.0	9	0.8%
BSD-2-Clause	7	0.6%
GPL-2.0	7	0.6%
LGPL-3.0	4	0.4%
Other values (5)	7	0.6%
(Missing)	551	49.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
mit	211	36.9%
gpl-3.0	163	28.5%
noassertion	73	12.8%
bsd-3-clause	49	8.6%
apache-2.0	29	5.1%
cc0-1.0	13	2.3%
agpl-3.0	9	1.6%
bsd-2-clause	7	1.2%
gpl-2.0	7	1.2%
lgpl-3.0	4	0.7%
Other values (5)	7	1.2%

Most occurring characters

Value	Count	Frequency (%)
-	348	9.0%
I	284	7.4%
T	284	7.4%
0	243	6.3%
.	230	6.0%
3	226	5.9%
M	212	5.5%
S	203	5.3%
L	188	4.9%
P	184	4.8%
Other values (26)	1454	37.7%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	2299	59.6%
Decimal Number	530	13.7%
Lowercase Letter	449	11.6%
Dash Punctuation	348	9.0%
Other Punctuation	230	6.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
I	284	12.4%
T	284	12.4%
M	212	9.2%
S	203	8.8%
L	188	8.2%
P	184	8.0%
G	183	8.0%
N	146	6.4%
O	146	6.4%
A	112	4.9%
Other values (7)	357	15.5%

Lowercase Letter

Value	Count	Frequency (%)
e	89	19.8%
a	87	19.4%
l	59	13.1%
s	59	13.1%
u	57	12.7%
c	31	6.9%
h	29	6.5%
p	29	6.5%
i	3	0.7%
r	2	0.4%
Other values (2)	4	0.9%

Decimal Number

Value	Count	Frequency (%)
0	243	45.8%
3	226	42.6%
2	45	8.5%
1	13	2.5%
4	3	0.6%

Dash Punctuation

Value	Count	Frequency (%)
-	348	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	230	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2748	71.3%
Common	1108	28.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
I	284	10.3%
T	284	10.3%
M	212	7.7%
S	203	7.4%
L	188	6.8%
P	184	6.7%
G	183	6.7%
N	146	5.3%
O	146	5.3%
A	112	4.1%
Other values (19)	806	29.3%

Common

Value	Count	Frequency (%)
-	348	31.4%
0	243	21.9%
.	230	20.8%
3	226	20.4%
2	45	4.1%
1	13	1.2%
4	3	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3856	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
-	348	9.0%
I	284	7.4%
T	284	7.4%
0	243	6.3%
.	230	6.0%
3	226	5.9%
M	212	5.5%
S	203	5.3%
L	188	4.9%
P	184	4.8%
Other values (26)	1454	37.7%

GitHub Description
Text

MISSING

Distinct	1057
Distinct (%)	98.9%
Missing	54
Missing (%)	4.8%
Memory size	8.9 KiB

Length

Max length	10997
Median length	343
Mean length	134.06642
Min length	7

Characters and Unicode

Total characters	143317
Distinct characters	111
Distinct categories	16 ?
Distinct scripts	5 ?
Distinct blocks	6 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1045 ?
Unique (%)	97.8%

Sample

1st row	Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
2nd row	The fundamental package for scientific computing with Python.
3rd row	Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing
4th row	DuckDB is an in-process SQL OLAP Database Management System
5th row	Apache Parquet

Value	Count	Frequency (%)
analysis	950	4.7%
of	791	3.9%
and	673	3.3%
the	669	3.3%
for	654	3.3%
cell	517	2.6%
single-cell	468	2.3%
data	451	2.2%
single	396	2.0%
a	366	1.8%
Other values (4025)	14177	70.5%

Most occurring characters

Value	Count	Frequency (%)
	19189	13.4%
e	12687	8.9%
a	9933	6.9%
i	9819	6.9%
n	8845	6.2%
s	8728	6.1%
l	8228	5.7%
o	7918	5.5%
t	7893	5.5%
r	6159	4.3%
Other values (101)	43918	30.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	111625	77.9%
Space Separator	19228	13.4%
Uppercase Letter	7159	5.0%
Other Punctuation	2195	1.5%
Dash Punctuation	1305	0.9%
Decimal Number	1194	0.8%
Close Punctuation	235	0.2%
Open Punctuation	229	0.2%
Math Symbol	51	< 0.1%
Final Punctuation	40	< 0.1%
Other values (6)	56	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	12687	11.4%
a	9933	8.9%
i	9819	8.8%
n	8845	7.9%
s	8728	7.8%
l	8228	7.4%
o	7918	7.1%
t	7893	7.1%
r	6159	5.5%
c	4959	4.4%
Other values (19)	26456	23.7%

Uppercase Letter

Value	Count	Frequency (%)
A	1116	15.6%
S	777	10.9%
R	737	10.3%
C	708	9.9%
N	606	8.5%
T	405	5.7%
D	359	5.0%
P	329	4.6%
I	320	4.5%
M	289	4.0%
Other values (16)	1513	21.1%

Other Punctuation

Value	Count	Frequency (%)
.	909	41.4%
,	624	28.4%
:	186	8.5%
/	173	7.9%
"	169	7.7%
%	40	1.8%
'	37	1.7%
;	18	0.8%
&	14	0.6%
!	7	0.3%
Other values (4)	18	0.8%

Other Symbol

Value	Count	Frequency (%)
▪	6	37.5%
🐟	1	6.2%
🏔	1	6.2%
🌍	1	6.2%
🍱	1	6.2%
🍣	1	6.2%
🦀	1	6.2%
🔬	1	6.2%
🧬	1	6.2%
🌸	1	6.2%

Decimal Number

Value	Count	Frequency (%)
2	262	21.9%
0	252	21.1%
1	207	17.3%
3	92	7.7%
9	86	7.2%
5	70	5.9%
7	70	5.9%
4	62	5.2%
8	48	4.0%
6	45	3.8%

Math Symbol

Value	Count	Frequency (%)
=	22	43.1%
+	15	29.4%
>	9	17.6%
<	4	7.8%
~	1	2.0%

Dash Punctuation

Value	Count	Frequency (%)
-	1302	99.8%
—	2	0.2%
–	1	0.1%

Space Separator

Value	Count	Frequency (%)
	19189	99.8%
	39	0.2%

Close Punctuation

Value	Count	Frequency (%)
)	232	98.7%
]	3	1.3%

Open Punctuation

Value	Count	Frequency (%)
(	226	98.7%
[	3	1.3%

Final Punctuation

Value	Count	Frequency (%)
’	32	80.0%
”	8	20.0%

Connector Punctuation

Value	Count	Frequency (%)
_	29	100.0%

Initial Punctuation

Value	Count	Frequency (%)
“	8	100.0%

Nonspacing Mark

Value	Count	Frequency (%)
️	1	100.0%

Other Letter

Value	Count	Frequency (%)
桜	1	100.0%

Currency Symbol

Value	Count	Frequency (%)
$	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	118783	82.9%
Common	24531	17.1%
Inherited	1	< 0.1%
Han	1	< 0.1%
Greek	1	< 0.1%

Most frequent character per script

Common

Value	Count	Frequency (%)
	19189	78.2%
-	1302	5.3%
.	909	3.7%
,	624	2.5%
2	262	1.1%
0	252	1.0%
)	232	0.9%
(	226	0.9%
1	207	0.8%
:	186	0.8%
Other values (44)	1142	4.7%

Latin

Value	Count	Frequency (%)
e	12687	10.7%
a	9933	8.4%
i	9819	8.3%
n	8845	7.4%
s	8728	7.3%
l	8228	6.9%
o	7918	6.7%
t	7893	6.6%
r	6159	5.2%
c	4959	4.2%
Other values (44)	33614	28.3%

Inherited

Value	Count	Frequency (%)
️	1	100.0%

Han

Value	Count	Frequency (%)
桜	1	100.0%

Greek

Value	Count	Frequency (%)
α	1	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	143204	99.9%
None	54	< 0.1%
Punctuation	51	< 0.1%
Geometric Shapes	6	< 0.1%
VS	1	< 0.1%
CJK	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	19189	13.4%
e	12687	8.9%
a	9933	6.9%
i	9819	6.9%
n	8845	6.2%
s	8728	6.1%
l	8228	5.7%
o	7918	5.5%
t	7893	5.5%
r	6159	4.3%
Other values (79)	43805	30.6%

None

Value	Count	Frequency (%)
	39	72.2%
ü	3	5.6%
🐟	1	1.9%
🏔	1	1.9%
🌍	1	1.9%
🍱	1	1.9%
🍣	1	1.9%
🦀	1	1.9%
é	1	1.9%
🔬	1	1.9%
Other values (4)	4	7.4%

Punctuation

Value	Count	Frequency (%)
’	32	62.7%
”	8	15.7%
“	8	15.7%
—	2	3.9%
–	1	2.0%

Geometric Shapes

Value	Count	Frequency (%)
▪	6	100.0%

VS

Value	Count	Frequency (%)
️	1	100.0%

CJK

Value	Count	Frequency (%)
桜	1	100.0%

GitHub Topics
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

GitHub Organization
Text

MISSING

Distinct	263
Distinct (%)	66.8%
Missing	729
Missing (%)	64.9%
Memory size	8.9 KiB

Length

Max length	37
Median length	28
Mean length	11.530457
Min length	3

Characters and Unicode

Total characters	4543
Distinct characters	57
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	203 ?
Unique (%)	51.5%

Sample

1st row	pandas-dev
2nd row	numpy
3rd row	apache
4th row	duckdb
5th row	apache

Value	Count	Frequency (%)
theislab	13	3.3%
ucdavis-bioinformatics-training	9	2.3%
teichlab	8	2.0%
broadinstitute	7	1.8%
scverse	6	1.5%
immunogenomics	5	1.3%
cytomining	5	1.3%
kharchenkolab	5	1.3%
icbi-lab	5	1.3%
oshlack	5	1.3%
Other values (253)	326	82.7%

Most occurring characters

Value	Count	Frequency (%)
a	481	10.6%
i	361	7.9%
e	331	7.3%
b	292	6.4%
l	286	6.3%
n	280	6.2%
o	260	5.7%
s	252	5.5%
r	213	4.7%
c	198	4.4%
Other values (47)	1589	35.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3910	86.1%
Uppercase Letter	458	10.1%
Dash Punctuation	162	3.6%
Decimal Number	13	0.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	481	12.3%
i	361	9.2%
e	331	8.5%
b	292	7.5%
l	286	7.3%
n	280	7.2%
o	260	6.6%
s	252	6.4%
r	213	5.4%
c	198	5.1%
Other values (16)	956	24.5%

Uppercase Letter

Value	Count	Frequency (%)
L	70	15.3%
C	48	10.5%
B	47	10.3%
S	37	8.1%
M	31	6.8%
I	30	6.6%
T	21	4.6%
G	20	4.4%
R	18	3.9%
A	18	3.9%
Other values (14)	118	25.8%

Decimal Number

Value	Count	Frequency (%)
2	3	23.1%
0	3	23.1%
1	3	23.1%
4	2	15.4%
9	1	7.7%
3	1	7.7%

Dash Punctuation

Value	Count	Frequency (%)
-	162	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4368	96.1%
Common	175	3.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	481	11.0%
i	361	8.3%
e	331	7.6%
b	292	6.7%
l	286	6.5%
n	280	6.4%
o	260	6.0%
s	252	5.8%
r	213	4.9%
c	198	4.5%
Other values (40)	1414	32.4%

Common

Value	Count	Frequency (%)
-	162	92.6%
2	3	1.7%
0	3	1.7%
1	3	1.7%
4	2	1.1%
9	1	0.6%
3	1	0.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4543	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	481	10.6%
i	361	7.9%
e	331	7.3%
b	292	6.4%
l	286	6.3%
n	280	6.2%
o	260	5.7%
s	252	5.5%
r	213	4.7%
c	198	4.4%
Other values (47)	1589	35.0%

GitHub Network Count
Real number (ℝ)

HIGH CORRELATION SKEWED ZEROS

Distinct	97
Distinct (%)	8.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	39.024043

Minimum	0
Maximum	16810
Zeros	435
Zeros (%)	38.7%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1
Q3	6
95-th percentile	54.8
Maximum	16810
Range	16810
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	575.00601
Coefficient of variation (CV)	14.73466
Kurtosis	691.19731
Mean	39.024043
Median Absolute Deviation (MAD)	1
Skewness	25.304196
Sum	43824
Variance	330631.91
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	435	38.7%
1	166	14.8%
2	103	9.2%
3	64	5.7%
4	45	4.0%
6	29	2.6%
5	25	2.2%
8	23	2.0%
9	20	1.8%
7	18	1.6%
Other values (87)	195	17.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	435	38.7%
1	166	14.8%
2	103	9.2%
3	64	5.7%
4	45	4.0%
5	25	2.2%
6	29	2.6%
7	18	1.6%
8	23	2.0%
9	20	1.8%

Value	Count	Frequency (%)
16810	1	0.1%
8647	1	0.1%
3096	1	0.1%
1332	1	0.1%
1157	1	0.1%
851	1	0.1%
536	1	0.1%
474	1	0.1%
473	1	0.1%
422	1	0.1%

GitHub Detected Languages
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Date Created
Date

UNIQUE

Distinct	1123
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Minimum	2010-08-24 01:37:33+00:00
Maximum	2023-10-10 14:24:36+00:00

Histogram

Histogram with fixed size bins (bins=50)

Date Most Recent Commit
Date

UNIQUE

Distinct	1123
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Minimum	2011-06-21 13:44:00+00:00
Maximum	2023-10-16 17:19:16+00:00

Histogram

Histogram with fixed size bins (bins=50)

Duration Created to Most Recent Commit
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Duration Created to Now
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Duration Most Recent Commit to Now
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

Repository Size (KB)
Real number (ℝ)

HIGH CORRELATION

Distinct	1010
Distinct (%)	89.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	75421.258

Minimum	1
Maximum	1922901
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	1
5-th percentile	16.1
Q1	688
median	10748
Q3	65047
95-th percentile	360260.2
Maximum	1922901
Range	1922900
Interquartile range (IQR)	64359

Descriptive statistics

Standard deviation	186112.08
Coefficient of variation (CV)	2.4676342
Kurtosis	39.984656
Mean	75421.258
Median Absolute Deviation (MAD)	10707
Skewness	5.5453982
Sum	84698073
Variance	3.4637706 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
6	10	0.9%
26	7	0.6%
13	6	0.5%
3	6	0.5%
67	5	0.4%
16	5	0.4%
24	5	0.4%
22	4	0.4%
30	4	0.4%
9	4	0.4%
Other values (1000)	1067	95.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	2	0.2%
2	2	0.2%
3	6	0.5%
4	3	0.3%
5	3	0.3%
6	10	0.9%
7	3	0.3%
8	3	0.3%
9	4	0.4%
10	1	0.1%

Value	Count	Frequency (%)
1922901	1	0.1%
1921765	1	0.1%
1792729	1	0.1%
1590023	1	0.1%
1496132	1	0.1%
1461986	1	0.1%
1447466	1	0.1%
1293566	1	0.1%
1245051	1	0.1%
1068214	1	0.1%

GitHub Repo Archived
Boolean

IMBALANCE

Distinct	2
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.2 KiB

False	1110
True	13

Common Values (Table)
Common Values (Plot)

Value	Count	Frequency (%)
False	1110	98.8%
True	13	1.2%

Duration Created to Now in Years
Real number (ℝ)

HIGH CORRELATION

Distinct	922
Distinct (%)	82.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.8459947

Minimum	0.016438356
Maximum	13.153425
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0.016438356
5-th percentile	0.64136986
Q1	2.2383562
median	3.5424658
Q3	5.2767123
95-th percentile	7.8227397
Maximum	13.153425
Range	13.136986
Interquartile range (IQR)	3.0383562

Descriptive statistics

Standard deviation	2.2608595
Coefficient of variation (CV)	0.5878478
Kurtosis	0.82630623
Mean	3.8459947
Median Absolute Deviation (MAD)	1.4767123
Skewness	0.76392392
Sum	4319.0521
Variance	5.1114857
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
4.142465753	4	0.4%
2.695890411	4	0.4%
0.7369863014	3	0.3%
0.8356164384	3	0.3%
4.383561644	3	0.3%
2.679452055	3	0.3%
3.682191781	3	0.3%
3.504109589	3	0.3%
5.520547945	3	0.3%
2.252054795	3	0.3%
Other values (912)	1091	97.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.01643835616	1	0.1%
0.09315068493	1	0.1%
0.09589041096	1	0.1%
0.1452054795	1	0.1%
0.1506849315	1	0.1%
0.1643835616	1	0.1%
0.1726027397	2	0.2%
0.1753424658	2	0.2%
0.2219178082	2	0.2%
0.2328767123	1	0.1%

Value	Count	Frequency (%)
13.15342466	1	0.1%
13.09589041	1	0.1%
13.07945205	1	0.1%
12.53972603	1	0.1%
12.21643836	1	0.1%
12.1369863	1	0.1%
12.07671233	1	0.1%
11.28767123	1	0.1%
11.09863014	1	0.1%
10.60821918	1	0.1%

Negative Duration Most Recent Commit to Now
Unsupported

REJECTED UNSUPPORTED

Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

category
Categorical

HIGH CORRELATION IMBALANCE

Distinct	5
Distinct (%)	0.4%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

github-query-result	1004
adjacent-tools	100
relevant-open-source	8
microscopy-analysis-tools	7
loi-focus	4

Length

Max length	25
Median length	19
Mean length	18.563669
Min length	9

Characters and Unicode

Total characters	20847
Distinct characters	23
Distinct categories	2 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	relevant-open-source
2nd row	relevant-open-source
3rd row	relevant-open-source
4th row	relevant-open-source
5th row	relevant-open-source

Common Values

Value	Count	Frequency (%)
github-query-result	1004	89.4%
adjacent-tools	100	8.9%
relevant-open-source	8	0.7%
microscopy-analysis-tools	7	0.6%
loi-focus	4	0.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
github-query-result	1004	89.4%
adjacent-tools	100	8.9%
relevant-open-source	8	0.7%
microscopy-analysis-tools	7	0.6%
loi-focus	4	0.4%

Most occurring characters

Value	Count	Frequency (%)
u	3024	14.5%
t	2223	10.7%
-	2142	10.3%
e	2140	10.3%
r	2031	9.7%
s	1144	5.5%
l	1130	5.4%
i	1022	4.9%
y	1018	4.9%
g	1004	4.8%
Other values (13)	3969	19.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	18705	89.7%
Dash Punctuation	2142	10.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
u	3024	16.2%
t	2223	11.9%
e	2140	11.4%
r	2031	10.9%
s	1144	6.1%
l	1130	6.0%
i	1022	5.5%
y	1018	5.4%
g	1004	5.4%
q	1004	5.4%
Other values (12)	2965	15.9%

Dash Punctuation

Value	Count	Frequency (%)
-	2142	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	18705	89.7%
Common	2142	10.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
u	3024	16.2%
t	2223	11.9%
e	2140	11.4%
r	2031	10.9%
s	1144	6.1%
l	1130	6.0%
i	1022	5.5%
y	1018	5.4%
g	1004	5.4%
q	1004	5.4%
Other values (12)	2965	15.9%

Common

Value	Count	Frequency (%)
-	2142	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	20847	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
u	3024	14.5%
t	2223	10.7%
-	2142	10.3%
e	2140	10.3%
r	2031	9.7%
s	1144	5.5%
l	1130	5.4%
i	1022	4.9%
y	1018	4.9%
g	1004	4.8%
Other values (13)	3969	19.0%

GitHub Stars (Log Scale)
Real number (ℝ)

HIGH CORRELATION MISSING ZEROS

Distinct	159
Distinct (%)	14.7%
Missing	44
Missing (%)	3.9%
Infinite	0
Infinite (%)	0.0%
Mean	1.7550269

Minimum	0
Maximum	10.597409
Zeros	316
Zeros (%)	28.1%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1.3862944
Q3	2.8903718
95-th percentile	5.3126267
Maximum	10.597409
Range	10.597409
Interquartile range (IQR)	2.8903718

Descriptive statistics

Standard deviation	1.7911075
Coefficient of variation (CV)	1.0205585
Kurtosis	1.3162256
Mean	1.7550269
Median Absolute Deviation (MAD)	1.3862944
Skewness	1.1530398
Sum	1893.674
Variance	3.2080662
Monotonicity	Decreasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	316	28.1%
0.6931471806	130	11.6%
1.098612289	88	7.8%
1.386294361	66	5.9%
1.609437912	39	3.5%
1.791759469	28	2.5%
2.079441542	24	2.1%
1.945910149	20	1.8%
2.197224577	18	1.6%
2.708050201	15	1.3%
Other values (149)	335	29.8%
(Missing)	44	3.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	316	28.1%
0.6931471806	130	11.6%
1.098612289	88	7.8%
1.386294361	66	5.9%
1.609437912	39	3.5%
1.791759469	28	2.5%
1.945910149	20	1.8%
2.079441542	24	2.1%
2.197224577	18	1.6%
2.302585093	10	0.9%

Value	Count	Frequency (%)
10.59740943	1	0.1%
10.11621707	1	0.1%
9.442562587	1	0.1%
9.424887076	1	0.1%
7.686621335	1	0.1%
7.578145472	1	0.1%
7.574045005	1	0.1%
7.555905094	1	0.1%
7.385230923	1	0.1%
7.372746366	1	0.1%

total lines of GitHub detected code
Real number (ℝ)

HIGH CORRELATION SKEWED

Distinct	1116
Distinct (%)	99.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9334464.7

Minimum	101
Maximum	2.2291975 × 10⁹
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	101
5-th percentile	6011.5
Q1	46763
median	195359
Q3	1562065
95-th percentile	32865361
Maximum	2.2291975 × 10⁹
Range	2.2291974 × 10⁹
Interquartile range (IQR)	1515302

Descriptive statistics

Standard deviation	75331005
Coefficient of variation (CV)	8.0702008
Kurtosis	689.29143
Mean	9334464.7
Median Absolute Deviation (MAD)	182408
Skewness	24.441818
Sum	1.0482604 × 10¹⁰
Variance	5.6747603 × 10¹⁵
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
954832	4	0.4%
50043	2	0.2%
102304	2	0.2%
7465	2	0.2%
3354	2	0.2%
22492093	1	0.1%
2459764	1	0.1%
60348	1	0.1%
41456	1	0.1%
60940	1	0.1%
Other values (1106)	1106	98.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
101	1	0.1%
397	1	0.1%
508	1	0.1%
547	1	0.1%
587	1	0.1%
695	1	0.1%
968	1	0.1%
1093	1	0.1%
1120	1	0.1%
1203	1	0.1%

Value	Count	Frequency (%)
2229197511	1	0.1%
880847605	1	0.1%
280960563	1	0.1%
277061560	1	0.1%
232185079	1	0.1%
192917347	1	0.1%
183885622	1	0.1%
182341397	1	0.1%
178105096	1	0.1%
166604099	1	0.1%

total lines of GitHub detected code (Log Scale)
Real number (ℝ)

HIGH CORRELATION

Distinct	1116
Distinct (%)	99.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12.554047

Minimum	4.6151205
Maximum	21.524907
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	4.6151205
5-th percentile	8.7014293
Q1	10.752846
median	12.182594
Q3	14.261488
95-th percentile	17.307912
Maximum	21.524907
Range	16.909787
Interquartile range (IQR)	3.5086417

Descriptive statistics

Standard deviation	2.6321878
Coefficient of variation (CV)	0.20966846
Kurtosis	-0.19078755
Mean	12.554047
Median Absolute Deviation (MAD)	1.6178114
Skewness	0.38674064
Sum	14098.195
Variance	6.9284124
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
13.76929069	4	0.4%
10.82063791	2	0.2%
11.53570405	2	0.2%
8.91798071	2	0.2%
8.117908942	2	0.2%
16.92867438	1	0.1%
14.71557597	1	0.1%
11.00788309	1	0.1%
10.6323879	1	0.1%
11.01764505	1	0.1%
Other values (1106)	1106	98.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
4.615120517	1	0.1%
5.983936281	1	0.1%
6.230481448	1	0.1%
6.304448802	1	0.1%
6.37502482	1	0.1%
6.543911846	1	0.1%
6.875232087	1	0.1%
6.996681488	1	0.1%
7.021083964	1	0.1%
7.092573716	1	0.1%

Value	Count	Frequency (%)
21.5249075	1	0.1%
20.59639519	1	0.1%
19.45372487	1	0.1%
19.43975028	1	0.1%
19.26304537	1	0.1%
19.0777724	1	0.1%
19.0298245	1	0.1%
19.0213913	1	0.1%
18.99788436	1	0.1%
18.93113089	1	0.1%

GitHub Forks (Log Scale)
Real number (ℝ)

HIGH CORRELATION MISSING ZEROS

Distinct	95
Distinct (%)	13.8%
Missing	435
Missing (%)	38.7%
Infinite	0
Infinite (%)	0.0%
Mean	1.6249093

Minimum	0
Maximum	9.7297292
Zeros	167
Zeros (%)	14.9%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0.69314718
median	1.3862944
Q3	2.4849066
95-th percentile	4.4343175
Maximum	9.7297292
Range	9.7297292
Interquartile range (IQR)	1.7917595

Descriptive statistics

Standard deviation	1.5268047
Coefficient of variation (CV)	0.93962453
Kurtosis	2.3275895
Mean	1.6249093
Median Absolute Deviation (MAD)	1.0116009
Skewness	1.254457
Sum	1117.9376
Variance	2.3311325
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	167	14.9%
0.6931471806	103	9.2%
1.098612289	64	5.7%
1.386294361	45	4.0%
1.791759469	30	2.7%
1.609437912	25	2.2%
2.079441542	23	2.0%
2.197224577	19	1.7%
1.945910149	18	1.6%
2.564949357	13	1.2%
Other values (85)	181	16.1%
(Missing)	435	38.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	167	14.9%
0.6931471806	103	9.2%
1.098612289	64	5.7%
1.386294361	45	4.0%
1.609437912	25	2.2%
1.791759469	30	2.7%
1.945910149	18	1.6%
2.079441542	23	2.0%
2.197224577	19	1.7%
2.302585093	10	0.9%

Value	Count	Frequency (%)
9.729729226	1	0.1%
9.064967719	1	0.1%
8.037866235	1	0.1%
7.194436851	1	0.1%
7.053585727	1	0.1%
6.746412129	1	0.1%
6.284134161	1	0.1%
6.161207322	1	0.1%
6.159095388	1	0.1%
6.045005314	1	0.1%

GitHub Open Issues (Log Scale)
Real number (ℝ)

HIGH CORRELATION MISSING ZEROS

Distinct	79
Distinct (%)	17.6%
Missing	674
Missing (%)	60.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.675776

Minimum	0
Maximum	8.270781
Zeros	125
Zeros (%)	11.1%
Negative	0
Negative (%)	0.0%
Memory size	8.9 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1.3862944
Q3	2.7080502
95-th percentile	4.5869563
Maximum	8.270781
Range	8.270781
Interquartile range (IQR)	2.7080502

Descriptive statistics

Standard deviation	1.6126548
Coefficient of variation (CV)	0.96233313
Kurtosis	1.2677127
Mean	1.675776
Median Absolute Deviation (MAD)	1.3862944
Skewness	1.0876703
Sum	752.42343
Variance	2.6006554
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	125	11.1%
0.6931471806	53	4.7%
1.098612289	33	2.9%
1.791759469	26	2.3%
1.386294361	26	2.3%
1.609437912	14	1.2%
2.079441542	14	1.2%
1.945910149	13	1.2%
2.397895273	8	0.7%
2.944438979	8	0.7%
Other values (69)	129	11.5%
(Missing)	674	60.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	125	11.1%
0.6931471806	53	4.7%
1.098612289	33	2.9%
1.386294361	26	2.3%
1.609437912	14	1.2%
1.791759469	26	2.3%
1.945910149	13	1.2%
2.079441542	14	1.2%
2.197224577	7	0.6%
2.302585093	6	0.5%

Value	Count	Frequency (%)
8.270781013	1	0.1%
8.204124933	1	0.1%
7.693025748	1	0.1%
6.926577033	1	0.1%
6.809039306	1	0.1%
6.552507887	1	0.1%
6.304448802	1	0.1%
6.049733455	1	0.1%
5.894402834	1	0.1%
5.733341277	1	0.1%

Primary language
Categorical

HIGH CORRELATION

Distinct	33
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Memory size	8.9 KiB

R	432
Python	218
Jupyter Notebook	195
HTML	113
MATLAB	49
Other values (28)	116

Length

Max length	24
Median length	17
Mean length	5.5556545
Min length	1

Characters and Unicode

Total characters	6239
Distinct characters	50
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	16 ?
Unique (%)	1.4%

Sample

1st row	Python
2nd row	Python
3rd row	C++
4th row	C++
5th row	Java

Common Values

Value	Count	Frequency (%)
R	432	38.5%
Python	218	19.4%
Jupyter Notebook	195	17.4%
HTML	113	10.1%
MATLAB	49	4.4%
Shell	16	1.4%
C++	15	1.3%
Java	15	1.3%
JavaScript	9	0.8%
Julia	9	0.8%
Other values (23)	52	4.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
r	432	32.6%
python	218	16.4%
jupyter	195	14.7%
notebook	195	14.7%
html	113	8.5%
matlab	49	3.7%
c	22	1.7%
shell	16	1.2%
java	15	1.1%
javascript	9	0.7%
Other values (29)	63	4.7%

Most occurring characters

Value	Count	Frequency (%)
o	826	13.2%
t	632	10.1%
e	441	7.1%
R	434	7.0%
y	414	6.6%
h	235	3.8%
J	233	3.7%
P	226	3.6%
n	225	3.6%
r	220	3.5%
Other values (40)	2353	37.7%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4054	65.0%
Uppercase Letter	1949	31.2%
Space Separator	204	3.3%
Math Symbol	30	0.5%
Dash Punctuation	1	< 0.1%
Other Punctuation	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
o	826	20.4%
t	632	15.6%
e	441	10.9%
y	414	10.2%
h	235	5.8%
n	225	5.6%
r	220	5.4%
u	209	5.2%
p	208	5.1%
k	199	4.9%
Other values (14)	445	11.0%

Uppercase Letter

Value	Count	Frequency (%)
R	434	22.3%
J	233	12.0%
P	226	11.6%
N	202	10.4%
T	170	8.7%
M	167	8.6%
L	164	8.4%
H	114	5.8%
A	100	5.1%
B	51	2.6%
Other values (12)	88	4.5%

Space Separator

Value	Count	Frequency (%)
	204	100.0%

Math Symbol

Value	Count	Frequency (%)
+	30	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	1	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6003	96.2%
Common	236	3.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
o	826	13.8%
t	632	10.5%
e	441	7.3%
R	434	7.2%
y	414	6.9%
h	235	3.9%
J	233	3.9%
P	226	3.8%
n	225	3.7%
r	220	3.7%
Other values (36)	2117	35.3%

Common

Value	Count	Frequency (%)
	204	86.4%
+	30	12.7%
-	1	0.4%
.	1	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6239	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
o	826	13.2%
t	632	10.1%
e	441	7.1%
R	434	7.0%
y	414	6.6%
h	235	3.8%
J	233	3.7%
P	226	3.6%
n	225	3.6%
r	220	3.5%
Other values (40)	2353	37.7%

Auto

Heatmap
Table

	GitHub Repository ID	GitHub Stars	GitHub Forks	GitHub Subscribers	GitHub Open Issues	GitHub Contributors	GitHub Network Count	Repository Size (KB)	Duration Created to Now in Years	GitHub Stars (Log Scale)	total lines of GitHub detected code	total lines of GitHub detected code (Log Scale)	GitHub Forks (Log Scale)	GitHub Open Issues (Log Scale)	GitHub License Type	GitHub Repo Archived	category	Primary language
GitHub Repository ID	1.000	-0.365	-0.415	-0.447	-0.305	-0.248	-0.415	-0.140	-1.000	-0.363	0.014	0.014	-0.415	-0.310	0.087	0.077	0.214	0.101
GitHub Stars	-0.365	1.000	0.819	0.644	0.685	0.536	0.817	0.398	0.365	1.000	0.249	0.249	0.857	0.695	0.000	0.000	0.404	0.134
GitHub Forks	-0.415	0.819	1.000	0.628	0.663	0.553	0.999	0.382	0.415	0.820	0.247	0.247	1.000	0.688	0.000	0.000	0.348	0.000
GitHub Subscribers	-0.447	0.644	0.628	1.000	0.589	0.559	0.625	0.350	0.447	0.642	0.228	0.228	0.651	0.599	0.000	0.000	0.348	0.079
GitHub Open Issues	-0.305	0.685	0.663	0.589	1.000	0.548	0.661	0.284	0.305	0.684	0.176	0.176	0.688	1.000	0.000	0.000	0.361	0.000
GitHub Contributors	-0.248	0.536	0.553	0.559	0.548	1.000	0.553	0.393	0.248	0.535	0.269	0.269	0.554	0.621	0.000	0.000	0.487	0.000
GitHub Network Count	-0.415	0.817	0.999	0.625	0.661	0.553	1.000	0.382	0.415	0.820	0.247	0.247	0.996	0.688	0.000	0.000	0.348	0.000
Repository Size (KB)	-0.140	0.398	0.382	0.350	0.284	0.393	0.382	1.000	0.140	0.394	0.534	0.534	0.287	0.299	0.000	0.000	0.046	0.285
Duration Created to Now in Years	-1.000	0.365	0.415	0.447	0.305	0.248	0.415	0.140	1.000	0.363	-0.014	-0.014	0.415	0.310	0.104	0.101	0.297	0.188
GitHub Stars (Log Scale)	-0.363	1.000	0.820	0.642	0.684	0.535	0.820	0.394	0.363	1.000	0.239	0.239	0.855	0.694	0.080	0.000	0.526	0.130
total lines of GitHub detected code	0.014	0.249	0.247	0.228	0.176	0.269	0.247	0.534	-0.014	0.239	1.000	1.000	0.188	0.262	0.000	0.000	0.000	0.558
total lines of GitHub detected code (Log Scale)	0.014	0.249	0.247	0.228	0.176	0.269	0.247	0.534	-0.014	0.239	1.000	1.000	0.188	0.262	0.080	0.114	0.081	0.375
GitHub Forks (Log Scale)	-0.415	0.857	1.000	0.651	0.688	0.554	0.996	0.287	0.415	0.855	0.188	0.188	1.000	0.689	0.088	0.000	0.526	0.115
GitHub Open Issues (Log Scale)	-0.310	0.695	0.688	0.599	1.000	0.621	0.688	0.299	0.310	0.694	0.262	0.262	0.689	1.000	0.000	0.019	0.457	0.039
GitHub License Type	0.087	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.104	0.080	0.000	0.080	0.088	0.000	1.000	0.000	0.229	0.181
GitHub Repo Archived	0.077	0.000	0.000	0.000	0.000	0.000	0.000	0.000	0.101	0.000	0.000	0.114	0.000	0.019	0.000	1.000	0.000	0.000
category	0.214	0.404	0.348	0.348	0.361	0.487	0.348	0.046	0.297	0.526	0.000	0.081	0.526	0.457	0.229	0.000	1.000	0.103
Primary language	0.101	0.134	0.000	0.079	0.000	0.000	0.000	0.285	0.188	0.130	0.558	0.375	0.115	0.039	0.181	0.000	0.103	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	Project Name	GitHub Repository ID	Project Homepage	Project Repo URL	Project Landscape Category	GitHub Stars	GitHub Forks	GitHub Subscribers	GitHub Open Issues	GitHub Contributors	GitHub License Type	GitHub Description	GitHub Topics	GitHub Organization	GitHub Network Count	GitHub Detected Languages	Date Created	Date Most Recent Commit	Duration Created to Most Recent Commit	Duration Created to Now	Duration Most Recent Commit to Now	Repository Size (KB)	GitHub Repo Archived	Duration Created to Now in Years	Negative Duration Most Recent Commit to Now	category	GitHub Stars (Log Scale)	total lines of GitHub detected code	total lines of GitHub detected code (Log Scale)	GitHub Forks (Log Scale)	GitHub Open Issues (Log Scale)	Primary language
0	pandas	858127	https://pandas.pydata.org	https://github.com/pandas-dev/pandas	[cytomining-ecosystem-relevant-open-source]	40031	16810	1121	3656	411	BSD-3-Clause	Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more	[alignment, data-analysis, data-science, flexible, pandas, python]	pandas-dev	16810	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 386224.0, 'C#': None, 'C++': None, 'CMake': None, 'CSS': 6804.0, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': 1277513.0, 'D': None, 'Dockerfile': 5751.0, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': 457000.0, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': 10664.0, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 20324063.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 14392.0, 'Singularity': None, 'Smarty': 8486.0, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': 1196.0, 'eC': None, 'sed': None}	2010-08-24 01:37:33+00:00	2023-10-16 16:52:20+00:00	4801 days 15:14:47	4801 days 15:45:14.559263	0 days 00:30:27.559263	334787	False	13.153425	-1 days +23:29:32.440737	relevant-open-source	10.597409	22492093.0	16.928674	9.729729	8.204125	Python
1	numpy	908607	https://numpy.org	https://github.com/numpy/numpy	[cytomining-ecosystem-relevant-open-source]	24741	8647	595	2193	435	BSD-3-Clause	The fundamental package for scientific computing with Python.	[numpy, python]	numpy	8647	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 6220071.0, 'C#': None, 'C++': 205725.0, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': 151476.0, 'D': 19.0, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': 3787.0, 'Fortran': 27683.0, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': 1697.0, 'Mako': None, 'Mercury': None, 'Meson': 88875.0, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 10458450.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 17058.0, 'Singularity': None, 'Smarty': 4129.0, 'Stan': None, 'Standard ML': None, 'Starlark': 1842.0, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': 5699.0}	2010-09-13 23:02:39+00:00	2023-10-16 14:25:39+00:00	4780 days 15:23:00	4780 days 18:20:08.559263	0 days 02:57:08.559263	131902	False	13.095890	-1 days +21:02:51.440737	relevant-open-source	10.116217	17186511.0	16.659635	9.064968	7.693026	Python
2	arrow	51905353	https://arrow.apache.org/	https://github.com/apache/arrow	[cytomining-ecosystem-relevant-open-source]	12614	3096	351	3908	367	Apache-2.0	Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing	[arrow]	apache	3096	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': 3709.0, 'Batchfile': 32824.0, 'C': 1507496.0, 'C#': 1525079.0, 'C++': 26864997.0, 'CMake': 732440.0, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': 1708430.0, 'D': None, 'Dockerfile': 135006.0, 'Emacs Lisp': 1064.0, 'Forth': None, 'Fortran': None, 'FreeMarker': 2312.0, 'Gnuplot': None, 'Go': 5619807.0, 'Groovy': None, 'HCL': None, 'HTML': 5604.0, 'Hack': None, 'ImageJ Macro': None, 'Java': 7353737.0, 'JavaScript': 128685.0, 'Jinja': 21888.0, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': 8771.0, 'M': None, 'M4': None, 'MATLAB': 722935.0, 'Makefile': 32659.0, 'Mako': None, 'Mercury': None, 'Meson': 62865.0, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': 11472.0, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 3288183.0, 'QMake': None, 'R': 1698163.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': 1794908.0, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 411936.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': 461913.0, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': 34537.0, 'TypeScript': 1108325.0, 'VBScript': None, 'Vala': 24798.0, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': 1256.0}	2016-02-17 08:00:23+00:00	2023-10-16 17:18:03+00:00	2798 days 09:17:40	2798 days 09:22:24.559263	0 days 00:04:44.559263	171101	False	7.665753	-1 days +23:55:15.440737	relevant-open-source	9.442563	55305799.0	17.828388	8.037866	8.270781	C++
3	duckdb	138754790	http://www.duckdb.org	https://github.com/duckdb/duckdb	[cytomining-ecosystem-relevant-open-source]	12393	1157	157	309	253	MIT	DuckDB is an in-process SQL OLAP Database Management System	[analytics, database, embedded-database, olap, sql]	duckdb	1157	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 1761733.0, 'C#': None, 'C++': 33576510.0, 'CMake': 146234.0, 'CSS': 182.0, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': 343518.0, 'JavaScript': 12990.0, 'Jinja': None, 'Julia': 250635.0, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': 14649.0, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 1407442.0, 'QMake': None, 'R': 1693.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 26187.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': 282562.0, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-06-26 15:04:45+00:00	2023-10-16 14:58:09+00:00	1937 days 23:53:24	1938 days 02:18:02.559263	0 days 02:24:38.559263	227662	False	5.309589	-1 days +21:35:21.440737	relevant-open-source	9.424887	37824335.0	17.448463	7.053586	5.733341	C++
4	parquet-mr	20675636		https://github.com/apache/parquet-mr	[cytomining-ecosystem-relevant-open-source]	2179	1332	95	130	190	Apache-2.0	Apache Parquet	[big-data, java, parquet]	apache	1332	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': 5923431.0, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 14771.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': 8436.0, 'Scheme': None, 'Scilab': None, 'Shell': 14860.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': 10354.0, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2014-06-10 07:00:07+00:00	2023-10-16 15:19:17+00:00	3415 days 08:19:10	3415 days 10:22:40.559263	0 days 02:03:30.559263	18475	False	9.356164	-1 days +21:56:29.440737	relevant-open-source	7.686621	5971852.0	15.602568	7.194437	4.867534	Java
5	snakemake	212840200	https://snakemake.readthedocs.io	https://github.com/snakemake/snakemake	[cytomining-ecosystem-relevant-open-source]	1955	474	22	906	280	MIT	This is the development home of the workflow management system Snakemake. For general information, see	[reproducibility, snakemake, workflow-management]	snakemake	474	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 1346.0, 'C#': None, 'C++': None, 'CMake': None, 'CSS': 3033.0, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': 1727.0, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': 3647966.0, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': 43973.0, 'Jinja': 6950.0, 'Julia': 334.0, 'Jupyter Notebook': 4389.0, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': 4400.0, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': 5.0, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 1336865.0, 'QMake': None, 'R': 786.0, 'Raku': None, 'Reason': None, 'Rebol': 6.0, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': 6.0, 'Ruby': None, 'Rust': 3617.0, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 5149.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': 5722.0, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2019-10-04 14:58:11+00:00	2023-10-16 09:50:35+00:00	1472 days 18:52:24	1473 days 02:24:36.559263	0 days 07:32:12.559263	92014	False	4.035616	-1 days +16:27:47.440737	relevant-open-source	7.578145	5066274.0	15.438116	6.161207	6.809039	HTML
6	seurat	35927665	http://www.satijalab.org/seurat	https://github.com/satijalab/seurat	[cytomining-ecosystem-adjacent-tools]	1947	851	78	229	83	NOASSERTION	R toolkit for single cell genomics	[cran, human-cell-atlas, single-cell-genomics, single-cell-rna-seq]	satijalab	851	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': 166.0, 'C#': None, 'C++': 103887.0, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': 1272988.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 942.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2015-05-20 05:23:02+00:00	2023-10-03 21:28:12+00:00	3058 days 16:05:10	3071 days 11:59:45.559263	12 days 19:54:35.559263	22722	False	8.413699	-13 days +04:05:24.440737	adjacent-tools	7.574045	1377983.0	14.136131	6.746412	5.433722	R
7	napari	144513571	https://napari.org	https://github.com/napari/napari	[microscopy-analysis-tools]	1912	389	49	1019	150	BSD-3-Clause	napari: a fast, interactive, multi-dimensional image viewer for python	[napari, numpy, python, visualization]	napari	389	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': 465.0, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': 6722.0, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 4637636.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': 2846.0, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 1221.0, 'Singularity': 95.0, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-08-13 01:12:28+00:00	2023-10-16 15:20:03+00:00	1890 days 14:07:35	1890 days 16:10:19.559263	0 days 02:02:44.559263	76654	False	5.178082	-1 days +21:57:15.440737	microscopy-analysis-tools	7.555905	4648985.0	15.352159	5.963579	6.926577	Python
8	scanpy	80342493	https://scanpy.readthedocs.io	https://github.com/scverse/scanpy	[cytomining-ecosystem-adjacent-tools]	1612	536	51	547	125	BSD-3-Clause	Single-cell analysis in Python. Scales to >1M cells.	[anndata, bioinformatics, data-science, machine-learning, python, scanpy, scverse, transcriptomics, visualize-data]	scverse	536	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 1292128.0, 'QMake': None, 'R': 2315.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2017-01-29 11:31:11+00:00	2023-10-16 15:40:34+00:00	2451 days 04:09:23	2451 days 05:51:36.559263	0 days 01:42:13.559263	39283	False	6.715068	-1 days +22:17:46.440737	adjacent-tools	7.385231	1294443.0	14.073591	6.284134	6.304449	Python
9	STAR	17778869		https://github.com/alexdobin/STAR	[cytomining-ecosystem-adjacent-tools]	1592	473	86	701	34	MIT	RNA-seq aligner	[]	None	473	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': 24345.0, 'Batchfile': None, 'C': 2350683.0, 'C#': None, 'C++': 1210764.0, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': 676.0, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 1006.0, 'Makefile': 25383.0, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': 11364.0, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': 295.0, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': 119547.0, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2014-03-15 15:47:05+00:00	2023-09-08 12:23:35+00:00	3463 days 20:36:30	3502 days 01:35:42.559263	38 days 04:59:12.559263	541229	False	9.594521	-39 days +19:00:47.440737	adjacent-tools	7.372746	3744063.0	15.135682	6.159095	6.552508	C

	Project Name	GitHub Repository ID	Project Homepage	Project Repo URL	Project Landscape Category	GitHub Subscribers	GitHub Contributors	GitHub License Type	GitHub Description	GitHub Topics	GitHub Organization	GitHub Detected Languages	Date Created	Date Most Recent Commit	Duration Created to Most Recent Commit	Duration Created to Now	Duration Most Recent Commit to Now	Repository Size (KB)	GitHub Repo Archived	Duration Created to Now in Years	Negative Duration Most Recent Commit to Now	category	GitHub Stars (Log Scale)	total lines of GitHub detected code	total lines of GitHub detected code (Log Scale)	GitHub Forks (Log Scale)	GitHub Open Issues (Log Scale)	Primary language
1113	BloodVesselImageAnalysis	323621577		https://github.com/RoopaMadhu/BloodVesselImageAnalysis	[related-tools-github-query-result]	1	1	None	Spatiographic projections of biological systems	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 188297.0, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2020-12-22 12:36:17+00:00	2020-12-22 14:22:59+00:00	0 days 01:46:42	1028 days 04:46:30.559263	1028 days 02:59:48.559263	576	False	2.816438	-1029 days +21:00:11.440737	github-query-result	NaN	188297.0	12.145776	NaN	NaN	MATLAB
1114	SickleCellDataAnalysis	298584969	None	https://github.com/ridz46/SickleCellDataAnalysis	[related-tools-github-query-result]	1	1	None	This repository contains the codes used for image processing and further downstream data analysis for the project on the development of a point-of-care diagnostic test for sickle cell disease. This repository is maintained by the Microfluidics & Biological Physics group, Department of Biosciences & Bioengineering, Indian Institute of Technology Bombay, Mumbai, India.	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': 4373.0, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2020-09-25 13:45:27+00:00	2020-09-28 08:55:24+00:00	2 days 19:09:57	1116 days 03:37:20.559263	1113 days 08:27:23.559263	17	False	3.057534	-1114 days +15:32:36.440737	github-query-result	NaN	4373.0	8.383205	NaN	NaN	R
1115	Data-Analysis-AMATH-482	245942374	None	https://github.com/priyanshir/Data-Analysis-AMATH-482	[related-tools-github-query-result]	1	1	None	Exploratory and objective data analysis methods applied to the physical, engineering, and biological sciences. Brief review of statistical methods and their computational implementation for studying time series analysis, spectral analysis, filtering methods, principal component analysis, orthogonal mode decomposition, and image processing and compression	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': 703573.0, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 33375.0, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2020-03-09 04:17:02+00:00	2020-03-14 22:41:50+00:00	5 days 18:24:48	1316 days 13:05:45.559263	1310 days 18:40:57.559263	2832	False	3.605479	-1311 days +05:19:02.440737	github-query-result	NaN	736948.0	13.510273	NaN	NaN	Jupyter Notebook
1116	Aging-Cell-Morphology-Cell-transformations-and-image-processing	235024426	None	https://github.com/sumisingh/Aging-Cell-Morphology-Cell-transformations-and-image-processing	[related-tools-github-query-result]	1	1	None	Identifying cellular transformations associated with aging using image processing	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': 8130261.0, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2020-01-20 05:18:57+00:00	2020-01-20 05:29:56+00:00	0 days 00:10:59	1365 days 12:03:50.559263	1365 days 11:52:51.559263	27874	False	3.739726	-1366 days +12:07:08.440737	github-query-result	NaN	8130261.0	15.911104	NaN	NaN	Jupyter Notebook
1117	CellMorphology	148259959		https://github.com/KnightofDawn/CellMorphology	[related-tools-github-query-result]	1	1	None	Python code to identify/analyze cells from microscopic stack images.	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 65906.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-09-11 04:25:09+00:00	2018-09-10 20:41:28+00:00	-1 days +16:16:19	1861 days 12:57:38.559263	1861 days 20:41:19.559263	161	False	5.098630	-1862 days +03:18:40.440737	github-query-result	NaN	65906.0	11.095985	NaN	NaN	Python
1118	ImagingCells	137526283	None	https://github.com/jesnyder/ImagingCells	[related-tools-github-query-result]	1	1	None	Scripts to analyze cell number and morphologies using images.	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': 1523.0, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-06-15 19:50:00+00:00	2018-08-31 19:21:33+00:00	76 days 23:31:33	1948 days 21:32:47.559263	1871 days 22:01:14.559263	1	False	5.336986	-1872 days +01:58:45.440737	github-query-result	NaN	1523.0	7.328437	NaN	NaN	Jupyter Notebook
1119	course-bia	119301640	None	https://github.com/denzf/course-bia	[related-tools-github-query-result]	1	1	MIT	Code examples for the course of Biological Image Analysis	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 6010.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-01-28 21:58:13+00:00	2018-01-24 03:22:19+00:00	-5 days +05:24:06	2086 days 19:24:34.559263	2091 days 14:00:28.559263	203	False	5.715068	-2092 days +09:59:31.440737	github-query-result	NaN	6010.0	8.701180	NaN	NaN	Python
1120	Cell-virulence-Detection-using-Image-Processing	163268436	None	https://github.com/arushigupta148/Cell-virulence-Detection-using-Image-Processing	[related-tools-github-query-result]	0	1	None	Designed an automated tool to find the thickness of multiple cell capsules from images using morphological operations to generate plots of cell size vs capsular thickness, simplifying detection of virulence in yeast cells for mycologists	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': None, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': 12989.0, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-12-27 08:27:06+00:00	2019-05-12 23:09:02+00:00	136 days 14:41:56	1754 days 08:55:41.559263	1617 days 18:13:45.559263	1751	False	4.805479	-1618 days +05:46:14.440737	github-query-result	NaN	12989.0	9.471858	NaN	NaN	Python
1121	Image-analysis	152904377		https://github.com/dguin/Image-analysis	[related-tools-github-query-result]	0	1	None	The repository contains code to analyze videos where each frame is a snapshot of the cellular status as a function of time. The program includes subroutines for segmentation protocols to pick a cell and differentiate it from the background when the signal to noise is low. The protocol docx explains what each code does and explains the order in which they must be run. As is the program analyzes FRET data from a cell, where the temperature increases as a function of time and one can evaluate the changes in the cell morphology as the cell is under heat stress	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 40670.0, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-10-13 18:53:42+00:00	2018-10-13 19:32:22+00:00	0 days 00:38:40	1828 days 22:29:05.559263	1828 days 21:50:25.559263	26	False	5.008219	-1829 days +02:09:34.440737	github-query-result	NaN	40670.0	10.613246	NaN	NaN	MATLAB
1122	oct-image-analysis	125785309		https://github.com/ricster101/oct-image-analysis	[related-tools-github-query-result]	0	1	None	Work developed with Adriana Costa during the course of Computer Vision and Biological Perception aiming to discover differences in mice retina	[]	None	{'AMPL': None, 'AspectJ': None, 'Assembly': None, 'Awk': None, 'Batchfile': None, 'C': None, 'C#': None, 'C++': None, 'CMake': None, 'CSS': None, 'Clojure': None, 'Common Workflow Language': None, 'Cuda': None, 'Cython': None, 'D': None, 'Dockerfile': None, 'Emacs Lisp': None, 'Forth': None, 'Fortran': None, 'FreeMarker': None, 'Gnuplot': None, 'Go': None, 'Groovy': None, 'HCL': None, 'HTML': None, 'Hack': None, 'ImageJ Macro': None, 'Java': None, 'JavaScript': None, 'Jinja': None, 'Julia': None, 'Jupyter Notebook': None, 'Kotlin': None, 'Lua': None, 'M': None, 'M4': None, 'MATLAB': 22755.0, 'Makefile': None, 'Mako': None, 'Mercury': None, 'Meson': None, 'Nextflow': None, 'Objective-C': None, 'Objective-C++': None, 'OpenEdge ABL': None, 'PHP': None, 'PLpgSQL': None, 'POV-Ray SDL': None, 'Perl': None, 'Perl 6': None, 'PostScript': None, 'PowerShell': None, 'Processing': None, 'Procfile': None, 'Python': None, 'QMake': None, 'R': None, 'Raku': None, 'Reason': None, 'Rebol': None, 'Ren'Py': None, 'Rich Text Format': None, 'Roff': None, 'Ruby': None, 'Rust': None, 'SCSS': None, 'Scala': None, 'Scheme': None, 'Scilab': None, 'Shell': None, 'Singularity': None, 'Smarty': None, 'Stan': None, 'Standard ML': None, 'Starlark': None, 'Swift': None, 'TSQL': None, 'TeX': None, 'Terra': None, 'Thrift': None, 'TypeScript': None, 'VBScript': None, 'Vala': None, 'Vim Script': None, 'Visual Basic .NET': None, 'Vue': None, 'WDL': None, 'XSLT': None, 'eC': None, 'sed': None}	2018-03-19 01:29:32+00:00	2018-03-19 03:31:25+00:00	0 days 02:01:53	2037 days 15:53:15.559263	2037 days 13:51:22.559263	16	False	5.580822	-2038 days +10:08:37.440737	github-query-result	NaN	22755.0	10.032540	NaN	NaN	MATLAB

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